Multi-Channel Light Detection and Ranging (LIDAR) Unit Having a Telecentric Lens Assembly and Single Circuit Board For Emitters and Detectors

ABSTRACT

A LIDAR unit includes a housing defining a cavity. The LIDAR unit further include a plurality of emitters disposed on a circuit board within the cavity. Each of the emitters emits a laser beam along a transmit path. The LIDAR system further includes a first telecentric lens assembly positioned within the cavity and along the transmit path such that the laser beam emitted from each of the plurality of emitters passes through the first telecentric lens assembly. The LIDAR further includes a second telecentric lens assembly positioned within the cavity and along a receive path such that a plurality of reflected laser beams entering the cavity pass through the second telecentric lens assembly. The first telecentric lens assembly and the second telecentric lens assembly each include a field flattening lens and at least one other lens.

RELATED APPLICATION

The present application is based on and claims benefit of U.S.Provisional Patent Application No. 63/059,190 having a filing date ofJul. 31, 2020, which is incorporated by reference herein.

FIELD

The present disclosure relates generally to LIDAR systems.

BACKGROUND

LIDAR systems use lasers to create three-dimensional representations ofsurrounding environments. A LIDAR system includes at least one emitterpaired with a receiver to form a channel, though an array of channelsmay be used to expand the field of view of the LIDAR system. Duringoperation, each channel emits a laser beam into the environment. Thelaser beam reflects off of an object within the surrounding environment,and the reflected laser beam is detected by the receiver. A singlechannel provides a single point of ranging information. Collectively,channels are combined to create a point cloud that corresponds to athree-dimensional representation of the surrounding environment. TheLIDAR system also includes circuitry to measure the time-of-flight (thatis, the elapsed time from emitting the laser beam to detecting thereflected laser beam). The time-of-flight measurement is used todetermine the distance of the LIDAR system to the object.

SUMMARY

Aspects and advantages of embodiments of the present disclosure will beset forth in part in the following description, or may be learned fromthe description, or may be learned through practice of the embodiments.

In one example aspect, a LIDAR system is provided. The LIDAR systemincludes a plurality of LIDAR units. Each of the plurality of LIDARunits includes a housing defining a cavity. Each of the plurality ofLIDAR units further includes a plurality of emitters disposed within thecavity. Each of the plurality of emitters is configured to emit a laserbeam. The LIDAR system includes a first optic comprising a prism diskrotatable about a first axis at a first rotational speed. The prism diskis positioned relative to the plurality of LIDAR units such that aplurality of laser beams exiting each of the plurality of LIDAR unitspass through the prism disk. The prism disk can be configured to refractthe plurality of laser beams. The LIDAR system includes a second opticrotatable about a second axis at a second rotational speed that isfaster than the first rotational speed. The second optic is positionedrelative to the first optic such that each of a plurality of refractedlaser beams exiting the prism disk reflect off of the second optic.

In another example aspect, an autonomous vehicle is provided. Theautonomous vehicle includes a LIDAR system coupled to a vehicle body ofthe autonomous vehicle. The LIDAR system includes a plurality of LIDARunits. Each of the plurality of LIDAR units includes a housing defininga cavity. Each of the plurality of LIDAR units further includes aplurality of emitters disposed within the cavity. Each of the pluralityof emitters is configured to emit a laser beam. The LIDAR systemincludes a prism disk rotatable about a first axis at a first rotationalspeed. The prism disk is positioned relative to the plurality of LIDARunits such that a plurality of laser beams exiting each of the pluralityof LIDAR units pass through the prism disk. The prism disk is configuredto refract the plurality of laser beams. The LIDAR system includes amirror rotatable about a second axis at a second rotational speed thatis faster than the first rotational speed. The mirror is positionedrelative to the prism disk such that each of a plurality of refractedlaser beams exiting the prism disk reflect off of the mirror.

In yet another example aspect, a LIDAR system is provided. The LIDARsystem includes a first LIDAR unit and a second LIDAR unit. The firstLIDAR unit and the second LIDAR unit each include a housing defining acavity. The first LIDAR unit and the second LIDAR unit each furtherinclude a plurality of emitters disposed within the cavity. Each of theplurality of emitters is configured to emit a laser beam. The LIDARsystem includes a first prism disk rotatable about a first axis at afirst rotational speed. The first prism disk is positioned relative tothe first LIDAR unit such that a plurality of laser beams emitted fromthe first LIDAR unit pass through the first prism disk. The first prismdisk is configured to refract the plurality of laser beams. The LIDARsystem includes a second prism disk rotatable about the first axis atthe first rotational speed. The second prism disk is positioned relativeto the second LIDAR unit such that a plurality of laser beams emittedfrom the second LIDAR unit pass through the second prism disk. Thesecond prism disk is configured to refract the plurality of laser beamsemitted from the second LIDAR unit. The LIDAR system includes a mirrorrotatable about a second axis at a second rotational speed that isfaster than the first rotational speed. The mirror is positionedrelative to the first prism disk and the second prism disk such that aplurality of refracted laser beams exiting each of the first prism diskand the second prism disk reflect off of the mirror.

Other example aspects of the present disclosure are directed to othersystems, methods, vehicles, apparatuses, tangible non-transitorycomputer-readable media, and devices for motion prediction and/oroperation of a device including a LIDAR system having a rotatable prismdisk for beam steering of lasers.

In one example aspect, a LIDAR unit is provided. The LIDAR unit includesa housing defining a cavity. The LIDAR unit includes a plurality ofemitters disposed on a surface of a circuit board positioned within thecavity. Each of the plurality of emitters is configured to emit a laserbeam along a transmit path. The LIDAR unit includes a first telecentriclens assembly positioned within the cavity and along the transmit pathsuch that the laser beam emitted from each of the plurality of emitterspasses through the first telecentric lens assembly. The firsttelecentric lens assembly includes a first field flattening lens and atleast one other lens. The LIDAR unit includes a second telecentric lensassembly positioned within the cavity and along a receive path such thata plurality of reflected laser beams entering the cavity pass throughthe second telecentric lens assembly. The second telecentric lensassembly includes a second field flattening lens and at least one otherlens. The LIDAR unit includes a plurality of detectors disposed on thesurface of the circuit board. Each of the plurality of detectors isspaced apart from a corresponding emitter of the plurality of emitters.Each of the plurality of detectors is configured to detect one or moreof the plurality of reflected laser beams.

In another example aspect, an autonomous vehicle is provided. Theautonomous vehicle includes one or more LIDAR units coupled to a vehiclebody of the autonomous vehicle. The one or more LIDAR units include ahousing defining a cavity. The one or more LIDAR units further include aplurality of emitters disposed on a surface of a circuit boardpositioned within the cavity. Each of the plurality of emitters includesa laser diode configured to emit a laser beam such that the laser beamis substantially perpendicular to the circuit board. Each of theplurality of emitters further include a collimation lens positionedrelative to the laser diode such that the laser beam emitted from thelaser diode reflects off of the collimation lens and along a transmitpath. The one or more LIDAR units include a first telecentric lensassembly positioned within the cavity and along the transmit path suchthat the laser beam emitted from each of the plurality of emitterspasses through the first telecentric lens assembly. The firsttelecentric lens assembly includes a first field flattening lens and atleast one other lens. The one or more LIDAR units include a secondtelecentric lens assembly positioned within the cavity and along areceive path such that a plurality of reflected laser beams entering thecavity pass through the second telecentric lens assembly. The secondtelecentric lens assembly includes a second field flattening lens and atleast one other lens. The one or more LIDAR units include a plurality ofdetectors disposed on the surface of the circuit board. Each of theplurality of detectors is spaced apart from a corresponding emitter ofthe plurality of emitters. Each of the plurality of detectors isconfigured to detect one or more of the plurality of reflected laserbeams.

In yet another example aspect, a computing system is provided. Thecomputing system includes one or more processors. The computing systemfurther includes one or more tangible, non-transitory, computer readablemedia that collectively store instructions that, when executed by theone or more processors, cause the computing system to performoperations. The operations include obtaining sensor data via a LIDARsystem. The LIDAR system includes a LIDAR unit. The LIDAR unit includesa housing defining a cavity. The LIDAR unit includes one or moreemitters positioned within the cavity. The one or more emitters areconfigured to emit one or more laser beams along a transmit path. TheLIDAR unit includes a first telecentric lens assembly along the transmitpath and a second telecentric lens assembly along a receive path. TheLIDAR unit includes one or more detectors configured to detect one ormore reflected laser beams entering the cavity. The operations furtherinclude determining an object within a field of view of the LIDAR systembased at least in part on the sensor data. The operations even furtherinclude determining one or more future locations of the object anddetermining an action for an autonomous vehicle based at least in parton the one or more future locations of the object

Other example aspects of the present disclosure are directed to othersystems, methods, vehicles, apparatuses, tangible non-transitorycomputer-readable media, and devices for motion prediction and/oroperation of a device including a LIDAR system having a telecentric lensassembly and single circuit board for both emitters and detectors.

The autonomous vehicle technology described herein can help improve thesafety of passengers of an autonomous vehicle, improve the safety of thesurroundings of the autonomous vehicle, improve the experience of therider and/or operator of the autonomous vehicle, as well as provideother improvements as described herein. Moreover, the autonomous vehicletechnology of the present disclosure can help improve the ability of anautonomous vehicle to effectively provide vehicle services to others andsupport the various members of the community in which the autonomousvehicle is operating, including persons with reduced mobility and/orpersons that are underserved by other transportation options.Additionally, the autonomous vehicle of the present disclosure mayreduce traffic congestion in communities as well as provide alternateforms of transportation that may provide environmental benefits.

These and other features, aspects and advantages of various embodimentswill become better understood with reference to the followingdescription and appended claims. The accompanying drawings, which areincorporated in and constitute a part of this specification, illustrateembodiments of the present disclosure and, together with thedescription, serve to explain the related principles.

BRIEF DESCRIPTION OF THE DRAWINGS

Detailed discussion of embodiments directed to one of ordinary skill inthe art are set forth in the specification, which makes reference to theappended figures, in which:

FIG. 1 depicts a block diagram of an example system for controlling thecomputational functions of an autonomous vehicle according to exampleembodiments of the present disclosure.

FIG. 2 depicts a LIDAR system according to example embodiments of thepresent disclosure.

FIG. 3 depicts a cross-sectional view of a LIDAR system according toexample embodiments of the present disclosure.

FIG. 4 depicts spacing between a plurality of laser beams exiting aLIDAR unit according to example embodiments of the present disclosure.

FIG. 5 depicts spacing between a plurality of laser beams exiting afirst optic of a LIDAR system according to example embodiments of thepresent disclosure.

FIG. 6 depicts a top-view of a first optic of a LIDAR system accordingto example embodiments of the present disclosure.

FIG. 7 depicts a cross-sectional view of a wedge of a first optic of aLIDAR system according to example embodiments of the present disclosure.

FIG. 8 depicts a side view of a plurality of laser beams exiting each ofa first LIDAR unit and a second LIDAR unit pass through a first optic ofa LIDAR system according to example embodiments of the presentdisclosure.

FIG. 9 depicts a front view of FIG. 12 according to example embodimentsof the present disclosure.

FIG. 10 depicts a LIDAR system according to example embodiments of thepresent disclosure.

FIG. 11 depicts a perspective view of the LIDAR system of FIG. 10according to example embodiments of the present disclosure.

FIG. 12 depicts another perspective view of the LIDAR system of FIG. 10according to example embodiments of the present disclosure.

FIG. 13 depicts a top view of the LIDAR system of FIG. 10 according toexample embodiments of the present disclosure.

FIG. 14 depicts spacing between a plurality of laser beams exiting aLIDAR unit of the LIDAR system of FIG. 10 according to exampleembodiments of the present disclosure.

FIG. 15 depicts spacing between a plurality of laser beams exiting afirst prism disk or a second prism disk of the LIDAR system of FIG. 10according to example embodiments of the present disclosure

FIG. 16 depicts an exploded view of a LIDAR unit of a LIDAR systemaccording to example embodiments of the present disclosure.

FIG. 17 depicts a cross-sectional view of a LIDAR unit of a LIDAR systemaccording to example embodiments of the present disclosure.

FIG. 18 depicts an emitter of the LIDAR unit in FIG. 10 according toexample embodiments of the present disclosure.

FIG. 19 depicts a laser diode of the emitter in FIG. 12 emitting a laserbeam according to example embodiments of the present disclosure.

FIG. 20 depicts an example computing system according to exampleembodiments of the present disclosure.

FIG. 21 depicts a block diagram of components of LIDAR system accordingto example embodiments of the present disclosure.

FIG. 22 depicts a flow diagram of a method of controlling operation ofan autonomous vehicle according to sensor data obtained from a LIDARsystem according to example embodiments of the present disclosure.

DETAILED DESCRIPTION

Example aspects of the present disclosure are directed to a lightdetection and ranging (LIDAR) system. The LIDAR system can include aplurality of LIDAR units. Each of the plurality of LIDAR units caninclude a housing defining a cavity. Each of the plurality of LIDARunits can further include a plurality of emitters disposed on a circuitboard positioned within the cavity. Each of the plurality of emitterscan be configured to emit a laser beam. In this manner, a plurality oflaser beams can be emitted from the housing of each of the plurality ofLIDAR units. The plurality of laser beams are spaced apart from oneanother by a first angular distance (e.g., greater than 4 degrees).

The LIDAR system according to example aspects of the present disclosurecan include a first optic. The first optic can include a prism diskrotatable about a first axis at a first rotational speed (e.g., from 500revolutions per minute to 700 revolutions per minute). The prism diskcan be positioned relative to the plurality of LIDAR units such that theplurality of laser beams pass through the prism disk. Furthermore, theprism disk can refract the plurality of laser beams to reduce a spacing(e.g., angular distance) between the plurality of laser beams to improvethe resolution of the LIDAR system. More specifically, the prism diskcan refract the plurality of laser beams such that a plurality ofrefracted laser beams exiting the prism disk are spaced apart from oneanother by a second angular distance (e.g., less than 2 degrees, lessthan 1 degree) that is less than the first angular distance.Construction of the prism disk will now be discussed in more detail.

The prism disk can include a plurality of wedges. For instance, in someimplementations, the prism disk can include a total of six wedges (e.g.,first wedge, second wedge, third wedge, fourth wedge, fifth wedge andsixth wedge). In alternative implementations, the prism disk can includemore or fewer wedges. Each of the plurality of wedges of the prism diskcan define a different wedge angle. For instance, a first wedge angleassociated with a first wedge of the plurality of wedges can bedifferent than a second wedge angle associated with a second wedge ofthe plurality of wedges. The wedge angle for each of the plurality ofwedges can range from −5 degrees relative to an axis (e.g., radial axis)of the prism disk to 5 degrees relative to the axis of the prism disk.

In some implementations, the plurality of laser beams exiting a firstLIDAR unit of the plurality of LIDAR units and the plurality of laserbeams exiting a second LIDAR unit of the plurality of LIDAR units canpass through a first portion of the prism disk. Conversely, theplurality of laser beams exiting a third LIDAR unit of the plurality ofLIDAR units and the plurality of laser beams exiting a fourth LIDAR unitof the plurality of LIDAR units can pass through a second portion of theprism disk. The second portion of the prism disk can be different thanthe first portion of the prism disk. For instance, the first portion caninclude a first wedge, a second wedge, and a third wedge. Conversely,the second portion can include the fourth wedge, the fifth wedge, andthe sixth wedge. Furthermore, in such implementations, each of thewedges (e.g., first wedge, second wedge, third wedge, fourth wedge,fifth wedge, sixth wedge) can be substantially the same size.

In some implementations, the housing of each of the plurality of LIDARunits can be tilted relative to the first axis by about 45 degrees. Forinstance, the housing of a first LIDAR unit and the housing of a secondLIDAR unit can each be tilted upward relative to the first axis.Conversely, the housing of a third LIDAR unit and the housing of afourth LIDAR unit can each be tilted downward relative to the firstaxis.

The LIDAR system according to example aspects of the present disclosurecan include a second optic positioned relative to the first optic suchthat the plurality of refracted laser beams reflect off of the secondoptic. In some implementations, the second optic can be a multi-sidedmirror (e.g., The second optic can be rotatable about a second axis at asecond rotational speed that is faster than the first rotational speed.For instance, in some implementations, the second rotational speed canrange from 3,300 revolutions per minute to 3,900 revolutions per minute.The second axis can, in some implementations, be substantiallyperpendicular (e.g., less than a 15 degree difference, less than a 10degree difference, less than a 5 degree difference, less than a 1 degreedifference, etc.) to the first axis.

A field of regard of the second optic can be wider than a field ofregard of the first optic. For instance, in some implementations, thefield of regard of the second optic can be about 180 degrees, whereasthe field of regard of the first optic can be about 80 degrees. In thismanner, the second optic can widen a field of regard of the LIDAR systemsuch that the LIDAR system can scan a larger area without needing tophysically move one or more of the LIDAR units. Construction of theLIDAR units of the LIDAR system will now be discussed in more detail.

Example aspects of the present disclosure are directed to a LIDAR unit.The LIDAR unit can include a housing defining a cavity. The LIDAR unitcan further include a plurality of emitters disposed on a surface of acircuit board positioned within the cavity. Each of the plurality ofemitters can be configured to emit a laser beam along a transmit paththat is substantially perpendicular to the surface of the circuit board.

Each of the plurality of emitters can include a laser diode configuredto emit the laser beam. In some implementations, the laser diode can beconfigured to emit the laser beam such that the laser beam issubstantially parallel (e.g., less than a 15 degree difference, lessthan a 10 degree difference, less than a 5 degree difference, less thana 1 degree difference, etc.) to the surface of the circuit board. Insuch implementations, each of the plurality of emitters can include acollimation lens. The collimation lens can be positioned relative to thelaser diode such that the laser beam reflects off of a surface of thecollimation lens. More specifically, the laser beam can reflect off ofthe surface such that the reflected laser beam is substantiallyperpendicular to the circuit board. In this manner, the reflected laserbeam can be directed along the transmit path.

The LIDAR unit can include a first telecentric lens assembly and asecond telecentric lens assembly. The first telecentric lens assemblycan be positioned within the cavity of the housing and along thetransmit path. In this manner, the laser beam emitted from each of theplurality of emitters can pass through the first telecentric lensassembly before exiting the cavity. Furthermore, the second telecentriclens assembly can be positioned within the cavity of the housing andalong a receive path. In this manner, a plurality of reflected laserbeams entering the cavity from an outside environment can pass throughthe second telecentric lens assembly.

It should be understood that the receive path along which the secondtelecentric lens assembly is positioned is different than the transmitpath along which the first telecentric lens assembly is positioned. Forinstance, the receive path can be located at a lower portion of thecavity, whereas the transmit path can be located at an upper portion ofthe cavity. Furthermore, in some implementations, the housing of theLIDAR unit can include a partition wall dividing the cavity into theupper portion and the lower portion.

The first telecentric lens assembly and the second telecentric lensassembly can each include multiple lenses. More specifically, the firsttelecentric lens assembly and the second telecentric lens assembly caneach include at least a first lens (e.g., field flattening lens) and asecond lens (e.g., refractive lens). The first lens (e.g., fieldflattening lens) can be positioned between the circuit board and thesecond lens (e.g., refractive lens). Furthermore, the first telecentriclens assembly can eliminate the need for the plurality of emitters to bedisposed on a curved surface. In this manner, the surface of the circuitboard on which the plurality of emitters are disposed can besubstantially flat (that is, not curved). This can reduce complexity inmanufacturing and assembly of the circuit board.

Furthermore, the field flattening lens of the first telecentric lensassembly disposed along the transmit path can be thinner than the fieldflattening lens of the field flattening lens of the second telecentriclens assembly disposed along the receive path. In some implementations,the field flattening lens of the first telecentric lens assembly canhave a thickness of about 3 millimeters, whereas the field flatteninglens of the second telecentric lens assembly can have a thickness ofabout 4 millimeters.

The LIDAR unit can include a plurality of detectors. Each of theplurality of detectors can be configured to detect one or more of theplurality of reflected laser beams entering the cavity. Furthermore,since the LIDAR unit includes the second telecentric lens assemblydisposed along the receive path, the plurality of detectors need not bedisposed on a curved surface. As such, the plurality of detectors can bedisposed on the same circuit board on which the plurality of emittersare disposed. More specifically, the plurality of emitters and theplurality of detectors can be disposed on the same surface of thecircuit board.

Each of the plurality of detectors can be spaced apart from acorresponding emitter of the plurality of emitters by a distance. Forinstance, in some implementations, each of the plurality of detectorscan be spaced from the corresponding emitter by a distance of about 4millimeters. As used herein, the term “about” refers to a range ofvalues with 20% of a stated numerical value. In some implementations,each of the plurality of detectors can include an avalanche photodiode.In some implementations, the LIDAR unit can include an optical filter.

The optical filter can be positioned along the receive path. Morespecifically, the optical filter can be positioned between thetelecentric lens of the receive optics and the plurality of detectors.In this manner, the optical filter can have a narrow acceptance angle(e.g., about 2 degrees), because the plurality of reflected laser beamsexiting the telecentric lens are substantially perpendicular to asurface of the optical filter. It should be understood that the opticalfilter can include any type of filter. For instance, in someimplementations, the optical filter can be a bandpass filter.

In some implementations, the LIDAR system according to the presentdisclosure can be implemented onboard an autonomous vehicle (e.g.,ground-based vehicle, aerial vehicle, etc.). The autonomous vehicle caninclude various systems and devices configured to control the operationof the autonomous vehicle. For example, the autonomous vehicle caninclude an onboard vehicle computing system (e.g., located on or withinthe autonomous vehicle) that is configured to operate the autonomousvehicle. The onboard vehicle computing system can obtain sensor datafrom sensor(s) onboard the vehicle (e.g., cameras, LIDAR, RADAR, etc.),attempt to comprehend the vehicle's surrounding environment byperforming various processing techniques on the sensor data, andgenerate an appropriate motion plan through the vehicle's surroundingenvironment. This can include, for example, detecting of object(s)(e.g., pedestrians, vehicles, bicycles/bicyclists, etc.) within thevehicle's surrounding environment, predicting the future motiontrajectory of those objects, and planning the vehicle's motion to avoidinterference with the object(s). Moreover, the autonomous vehicle caninclude a communications system that can allow the autonomous vehicle tocommunicate with a computing system that is remote from the autonomousvehicle such as, for example, that of a service entity.

An autonomous vehicle can perform vehicle services for one or moreservice entities. A service entity can be associated with the provisionof one or more vehicle services. For example, a service entity can be anindividual, a group of individuals, a company (e.g., a business entity,organization, etc.), a group of entities (e.g., affiliated companies),and/or another type of entity that offers and/or coordinates theprovision of vehicle service(s) to one or more users. As an example, aservice entity can offer vehicle service(s) to users via a softwareapplication (e.g., on a user computing device), via a website, and/orvia other types of interfaces that allow a user to request a vehicleservice. The vehicle services can include user transportation services(e.g., by which the vehicle transports user(s) from one location toanother), delivery services (e.g., by which a vehicle delivers item(s)to a requested destination location), courier services (e.g., by which avehicle retrieves item(s) from a requested origin location and deliversthe item to a requested destination location), and/or other types ofservices.

An operations computing system of the service entity can help tocoordinate the performance of vehicle services by autonomous vehicles.For instance, the operations computing system can include a serviceplatform. The service platform can include a plurality of back-endservices and front-end interfaces, which are accessible via one or moreAPIs. For example, an autonomous vehicle and/or another computing systemthat is remote from the autonomous vehicle can communicate/access theservice platform (and its backend services) by calling the one or moreAPIs. Such components can facilitate secure, bidirectionalcommunications between autonomous vehicles and/or the service entity'soperations system (e.g., including a data center, etc.).

The service platform can allow an autonomous vehicle to obtain data fromand/or communicate data to the operations computing system. By way ofexample, a user can provide (e.g., via a user device) a request for avehicle service to the operations computing system associated with theservice entity. The request can indicate the type of vehicle servicethat the user desires (e.g., a user transportation service, a deliveryservice, etc.), one or more locations (e.g., an origin, destination,etc.), timing constraints (e.g., pick-up time, drop-off time, deadlines,etc.), a number of user(s) and/or items to be transported in thevehicle, other service parameters (e.g., a need for handicap access,handle with care instructions, etc.), and/or other information. Theoperations computing system of the service entity can process therequest and identify one or more autonomous vehicles that may be able toperform the requested vehicle services for the user. For instance, theoperations computing system can identify which autonomous vehicle(s) areonline with the service entity (e.g., available for a vehicle serviceassignment, addressing a vehicle service assignment, etc.). Anautonomous vehicle can go online with a service entity by, for example,connecting with the service entity's operations computing system (e.g.,the service platform) so that the vehicle computing system cancommunicate with the operations computing system via a network. Onceonline, the operations computing system can communicate a vehicleservice assignment indicative of the requested vehicle services and/orother data to the autonomous vehicle.

The autonomous vehicle can be configured to operate in one or more modesincluding, for example, a fully autonomous operating mode, asemi-autonomous operating mode, and a manual operating mode. The fullyautonomous (e.g., self-driving) operating mode can be one in which theautonomous vehicle can provide driving and navigational operation withminimal and/or no interaction from a human driver present in theautonomous vehicle. The semi-autonomous operating mode can be one inwhich the vehicle can operate with some interaction from a human driverpresent in the vehicle. The manual operating mode can be one in which ahuman driver present in the autonomous vehicle manually controls (e.g.,acceleration, braking, steering) the autonomous vehicle via one or moreinput devices (e.g., steering device) of the autonomous vehicle.

The LIDAR system can be implemented on the autonomous vehicle to obtaindata associated with the surrounding environment in which the autonomousvehicle is operating (e.g., while online with service entity, performinga vehicle service, etc.). In some implementations, the LIDAR system canbe coupled to a vehicle body (e.g., frame, panels, etc.) of theautonomous vehicle. For instance, the LIDAR system can be coupled to abumper of the autonomous vehicle. However, it should be understood thatthe LIDAR system can be mounted to the autonomous vehicle at anysuitable location.

An autonomous vehicle can utilize the described LIDAR system to accountfor object(s) within a field-of view of the LIDAR system. For instance,an autonomous vehicle (e.g., its onboard computing system) can obtainsensor data via the LIDAR system. The sensor data can be indicative ofan object within the field of view of the LIDAR system. The autonomousvehicle can determine perception data for the object within the field ofview of the LIDAR system based at least in part on the sensor data. Theperception data can describe, for example, an estimate of the object'scurrent and/or past: location and/or position; speed; velocity;acceleration; heading; orientation; size/footprint (e.g., as representedby a bounding shape); class (e.g., pedestrian class vs. vehicle classvs. bicycle class); and/or other state information. The autonomousvehicle can determine future location(s) of the object based at least inpart on the perception data. For example, the autonomous vehicle cangenerate a trajectory (e.g., including one or more waypoints) that isindicative of a predicted future motion of the object, given theobject's heading, velocity, type, etc. over current/previoustimestep(s). The autonomous vehicle can determine an action for theautonomous vehicle based at least in part on the detected object and/orthe future location(s) of the object within the field of view of theLIDAR system. For example, the autonomous vehicle can generate a motionplan that includes a vehicle trajectory by which the vehicle can travelto avoid interfering/colliding with the object. In another example, theautonomous vehicle can determine that the object is a user that intendsto enter the autonomous vehicle (e.g., for a human transportationservice) and/or that intends place an item in the autonomous vehicle(e.g., for a courier/delivery service). The autonomous vehicle canunlock a door, trunk, etc. to allow the user to enter and/or place anitem within the vehicle. The autonomous vehicle can communicate one ormore control signals (e.g., to a motion control system, door controlsystem, etc.) to initiate the determined actions.

A LIDAR system according to example embodiments of the presentdisclosure can provide numerous technical effects and benefits. Forinstance, the prism disk of the LIDAR system can refract the pluralityof laser beams exiting each of the plurality of LIDAR units such thatthe spacing (e.g., angular distance) between the plurality of refractedlaser beams exiting the first optic is less than the spacing (e.g.,angular distance) between the plurality of laser beams exiting each ofthe plurality of LIDAR units. In this manner, the resolution of theLIDAR system according to the present disclosure can be improved.Furthermore, the second optic of the LIDAR system can be positioned suchthat the plurality of refracted laser beams exiting the first opticreflect off of the second optic and widen the field of regard of theLIDAR system. In this manner, the LIDAR system according to the presentdisclosure can scan a larger area without needing to manipulate (e.g.,move) one or more LIDAR units of the system.

Additionally, a LIDAR unit according to the present disclosure canprovide numerous technical effects and benefits. For instance, thetransmit optics and receive optics of the LIDAR unit can each include atelecentric lens. The telecentric lens allows the emitters and detectorsof the LIDAR unit to be disposed on the same circuit board. Morespecifically, the telecentric lens allows the emitters and detectors ofthe LIDAR unit to be disposed on the same surface of the circuit board.Furthermore, since the transmit optics and the receive optics eachinclude the telecentric lens, the surface of the circuit board can besubstantially flat. In this manner, the circuit board can be more easilymanufactured. Moreover, the telecentric can allow for the use of anoptical filter having a narrow acceptance angle (e.g., about 2 degrees)while still maintaining a wide field-of view out of the cavity of theLIDAR unit.

Referring now to the FIGS., FIG. 1 depicts a system 100 that includes acommunications network 102; an operations computing system 104; one ormore remote computing devices 106; a vehicle 108; a vehicle computingsystem 112; one or more sensors 114; sensor data 116; a positioningsystem 118; an autonomy computing system 120; map data 122; a perceptionsystem 124; a prediction system 126; a motion planning system 128;perception data 130; prediction data 132; motion plan data 134; acommunication system 136; a vehicle control system 138; and ahuman-machine interface 140.

The operations computing system 104 can be associated with a serviceprovider that can provide one or more vehicle services to a plurality ofusers via a fleet of vehicles that includes, for example, the vehicle108. The vehicle services can include transportation services (e.g.,rideshare services), courier services, delivery services, and/or othertypes of services.

The operations computing system 104 can include multiple components forperforming various operations and functions. For example, the operationscomputing system 104 can be configured to monitor and communicate withthe vehicle 108 and/or its users to coordinate a vehicle serviceprovided by the vehicle 108. To do so, the operations computing system104 can communicate with the one or more remote computing devices 106and/or the vehicle 108 via one or more communications networks includingthe communications network 102. The communications network 102 can sendand/or receive signals (e.g., electronic signals) or data (e.g., datafrom a computing device) and include any combination of various wired(e.g., twisted pair cable) and/or wireless communication mechanisms(e.g., cellular, wireless, satellite, microwave, and radio frequency)and/or any desired network topology (or topologies). For example, thecommunications network 102 can include a local area network (e.g.intranet), wide area network (e.g. the Internet), wireless LAN network(e.g., via Wi-Fi), cellular network, a SATCOM network, VHF network, a HFnetwork, a WiMAX based network, and/or any other suitable communicationsnetwork (or combination thereof) for transmitting data to and/or fromthe vehicle 108.

Each of the one or more remote computing devices 106 can include one ormore processors and one or more memory devices. The one or more memorydevices can be used to store instructions that when executed by the oneor more processors of the one or more remote computing devices 106 causethe one or more processors to perform operations and/or functionsincluding operations and/or functions associated with the vehicle 108including sending and/or receiving data or signals to and from thevehicle 108, monitoring the state of the vehicle 108, and/or controllingthe vehicle 108. The one or more remote computing devices 106 cancommunicate (e.g., exchange data and/or signals) with one or moredevices including the operations computing system 104 and the vehicle108 via the communications network 102. For example, the one or moreremote computing devices 106 can request the location of the vehicle 108or a state of one or more objects detected by the one or more sensors114 of the vehicle 108, via the communications network 102.

The one or more remote computing devices 106 can include one or morecomputing devices (e.g., a desktop computing device, a laptop computingdevice, a smart phone, and/or a tablet computing device) that canreceive input or instructions from a user or exchange signals or datawith an item or other computing device or computing system (e.g., theoperations computing system 104). Further, the one or more remotecomputing devices 106 can be used to determine and/or modify one or morestates of the vehicle 108 including a location (e.g., a latitude andlongitude), a velocity, an acceleration, a trajectory, a heading, and/ora path of the vehicle 108 based, at least in part, on signals or dataexchanged with the vehicle 108. In some implementations, the operationscomputing system 104 can include the one or more remote computingdevices 106.

The vehicle 108 can be a ground-based vehicle (e.g., an automobile, amotorcycle, a train, a tram, a bus, a truck, a tracked vehicle, a lightelectric vehicle, a moped, a scooter, and/or an electric bicycle), anaircraft (e.g., airplane or helicopter), a boat, a submersible vehicle(e.g., a submarine), an amphibious vehicle, a hovercraft, a roboticdevice (e.g. a bipedal, wheeled, or quadrupedal robotic device), and/orany other type of vehicle. The vehicle 108 can be an autonomous vehiclethat can perform various actions including driving, navigating, and/oroperating, with minimal and/or no interaction from a human driver. Thevehicle 108 can be configured to operate in one or more modes including,for example, a fully autonomous operational mode, a semi-autonomousoperational mode, a manual operating mode, a park mode, and/or a sleepmode. A fully autonomous (e.g., self-driving) operational mode can beone in which the vehicle 108 can provide driving and navigationaloperation with minimal and/or no interaction from a human driver presentin the vehicle. A semi-autonomous operational mode can be one in whichthe vehicle 108 can operate with some interaction from a human driverpresent in the vehicle. A manual operating mode can be one in which ahuman driver present in the autonomous vehicle manually controls (e.g.,acceleration, braking, steering) the vehicle 108 via one or more vehiclecontrol devices (e.g., steering device) of the vehicle 108. Park and/orsleep modes can be used between operational modes while the vehicle 108performs various actions including waiting to provide a subsequentvehicle service, and/or recharging between operational modes.

An indication, record, and/or other data indicative of the state of thevehicle 108, the state of one or more passengers of the vehicle 108,and/or the state of an environment external to the vehicle 108 includingone or more objects (e.g., the physical dimensions, velocity,acceleration, heading, location, and/or appearance of the one or moreobjects) can be stored locally in one or more memory devices of thevehicle 108. Furthermore, as discussed above, the vehicle 108 canprovide data indicative of the state of the one or more objects (e.g.,physical dimensions, velocity, acceleration, heading, location, and/orappearance of the one or more objects) within a predefined distance ofthe vehicle 108 to the operations computing system 104 and/or the remotecomputing devices 106, which can store an indication, record, and/orother data indicative of the state of the one or more objects within apredefined distance of the vehicle 108 in one or more memory devicesassociated with the operations computing system 104 and/or the one ormore remote computing devices 106 (e.g., remote from the vehicle).

The vehicle 108 can include and/or be associated with the vehiclecomputing system 112. The vehicle computing system 112 can include oneor more computing devices located onboard the vehicle 108. For example,the one or more computing devices of the vehicle computing system 112can be located on and/or within the vehicle 108. The one or morecomputing devices of the vehicle computing system 112 can includevarious components for performing various operations and functions. Forinstance, the one or more computing devices of the vehicle computingsystem 112 can include one or more processors and one or more tangiblenon-transitory, computer readable media (e.g., memory devices). The oneor more tangible non-transitory, computer readable media can storeinstructions that when executed by the one or more processors cause thevehicle 108 (e.g., its computing system, one or more processors, andother devices in the vehicle 108) to perform operations and/orfunctions, including those described herein for accessing state dataincluding information associated with one or more respective locationsand/or characteristics of one or more objects over a plurality of timeintervals and/or determining, based at least in part on the state dataand a machine-learned prediction generator model, one or more predictedtrajectories of the one or more objects at one or more subsequent timeintervals following the plurality of time intervals. Furthermore, thevehicle computing system 112 can perform one or more operationsassociated with the control, exchange of data, and/or operation ofvarious devices and systems including robotic devices and/or othercomputing devices.

As depicted in FIG. 1, the vehicle computing system 112 can include theone or more sensors 114; the positioning system 118; the autonomycomputing system 120; the communication system 136; the vehicle controlsystem 138; and the human-machine interface 140. One or more of thesesystems can be configured to communicate with one another via acommunication channel. The communication channel can include one or moredata buses (e.g., controller area network (CAN)), on-board diagnosticsconnector (e.g., OBD-II), and/or a combination of wired and/or wirelesscommunication links. The onboard systems can exchange (e.g., send and/orreceive) data, messages, and/or signals amongst one another via thecommunication channel.

The one or more sensors 114 can be configured to generate and/or storedata including the sensor data 116 associated with one or more objectsproximate to the vehicle 108 (e.g., within range or a field of view ofone or more of the one or more sensors 114). The one or more sensors 114can include one or more Light Detection and Ranging (LiDAR) systems, oneor more Radio Detection and Ranging (RADAR) systems, one or more cameras(e.g., visible spectrum cameras and/or infrared cameras), one or moresonar systems, one or more motion sensors, and/or other types of imagecapture devices and/or sensors. The sensor data 116 can include imagedata, radar data, LiDAR data, sonar data, and/or other data acquired bythe one or more sensors 114. The one or more objects can include, forexample, pedestrians, vehicles, bicycles, buildings, roads, foliage,utility structures, bodies of water, and/or other objects. The one ormore objects can be located on or around (e.g., in the area surroundingthe vehicle 108) various parts of the vehicle 108 including a frontside, rear side, left side, right side, top, or bottom of the vehicle108. The sensor data 116 can be indicative of a location of the one ormore objects within the surrounding environment of the vehicle 108 atone or more times. For example, sensor data 116 can be indicative of oneor more LiDAR point clouds associated with the one or more objectswithin the surrounding environment. The one or more sensors 114 canprovide the sensor data 116 to the autonomy computing system 120.

In addition to the sensor data 116, the autonomy computing system 120can retrieve or otherwise obtain data, including the map data 122. Themap data 122 can provide detailed information about the surroundingenvironment of the vehicle 108. For example, the map data 122 canprovide information regarding: the identity and/or location of differentroadways, road segments, buildings, or other items or objects (e.g.,lampposts, crosswalks and/or curbs); the location and directions oftraffic lanes (e.g., the location and direction of a parking lane, aturning lane, a bicycle lane, or other lanes within a particular roadwayor other travel way and/or one or more boundary markings associatedtherewith); traffic control data (e.g., the location and instructions ofsignage, traffic lights, or other traffic control devices); and/or anyother map data that provides information that assists the vehiclecomputing system 112 in processing, analyzing, and perceiving itssurrounding environment and its relationship thereto.

The positioning system 118 can determine a current position of thevehicle 108. The positioning system 118 can be any device or circuitryfor analyzing the position of the vehicle 108. For example, thepositioning system 118 can determine a position by using one or more ofinertial sensors, a satellite positioning system, based on IP/MACaddress, by using triangulation and/or proximity to network accesspoints or other network components (e.g., cellular towers and/or Wi-Fiaccess points) and/or other suitable techniques. The position of thevehicle 108 can be used by various systems of the vehicle computingsystem 112 and/or provided to one or more remote computing devices(e.g., the operations computing system 104 and/or the remote computingdevices 106). For example, the map data 122 can provide the vehicle 108relative positions of the surrounding environment of the vehicle 108.The vehicle 108 can identify its position within the surroundingenvironment (e.g., across six axes) based at least in part on the datadescribed herein. For example, the vehicle 108 can process the sensordata 116 (e.g., LiDAR data, camera data) to match it to a map of thesurrounding environment to get a determination of the vehicle's positionwithin that environment (e.g., transpose the vehicle's position withinits surrounding environment).

The autonomy computing system 120 can include a perception system 124, aprediction system 126, a motion planning system 128, and/or othersystems that cooperate to perceive the surrounding environment of thevehicle 108 and determine a motion plan for controlling the motion ofthe vehicle 108 accordingly. One or more of these systems can becombined into a single system performing the functions thereof and/orshare computing resources. For example, the autonomy computing system120 can receive the sensor data 116 from the one or more sensors 114,attempt to determine the state of the surrounding environment byperforming various processing techniques on the sensor data 116 (and/orother data), and generate an appropriate motion plan through thesurrounding environment, including for example, a motion plan thatnavigates the vehicle 108 around the current and/or predicted locationsof one or more objects detected by the one or more sensors 114. Theautonomy computing system 120 can control the one or more vehiclecontrol systems 138 to operate the vehicle 108 according to the motionplan.

The autonomy computing system 120 can identify one or more objects thatare proximate to the vehicle 108 based at least in part on the sensordata 116 and/or the map data 122. For example, the perception system 124can obtain perception data 130 descriptive of a current and/or paststate of an object that is proximate to the vehicle 108. The perceptiondata 130 for each object can describe, for example, an estimate of theobject's current and/or past: location and/or position; speed; velocity;acceleration; heading; orientation; size/footprint (e.g., as representedby a bounding shape); class (e.g., pedestrian class vs. vehicle classvs. bicycle class), and/or other state information. The perceptionsystem 124 can provide the perception data 130 to the prediction system126 (e.g., for predicting the movement of an object).

The prediction system 126 can generate prediction data 132 associatedwith each of the respective one or more objects proximate to the vehicle108. The prediction data 132 can be indicative of one or more predictedfuture locations of each respective object. The prediction data 132 canbe indicative of a predicted path (e.g., predicted trajectory) of atleast one object within the surrounding environment of the vehicle 108.For example, the predicted path (e.g., trajectory) can indicate a pathalong which the respective object is predicted to travel over time(and/or the velocity at which the object is predicted to travel alongthe predicted path). The prediction system 126 can provide theprediction data 132 associated with the one or more objects to themotion planning system 128.

In some implementations, the prediction system 126 can utilize one ormore machine-learned models. For example, the prediction system 126 candetermine prediction data 132 including a predicted trajectory (e.g., apredicted path, one or more predicted future locations, etc.) alongwhich a respective object is predicted to travel over time based on oneor more machine-learned models. By way of example, the prediction system126 can generate such predictions by including, employing, and/orotherwise leveraging a machine-learned prediction model. For example,the prediction system 126 can receive perception data 130 (e.g., fromthe perception system 124) associated with one or more objects withinthe surrounding environment of the vehicle 108. The prediction system126 can input the perception data 130 (e.g., BEV image, LIDAR data,etc.) into the machine-learned prediction model to determinetrajectories of the one or more objects based on the perception data 130associated with each object. For example, the machine-learned predictionmodel can be previously trained to output a future trajectory (e.g., afuture path, one or more future geographic locations, etc.) of an objectwithin a surrounding environment of the vehicle 108. In this manner, theprediction system 126 can determine the future trajectory of the objectwithin the surrounding environment of the vehicle 108 based, at least inpart, on the machine-learned prediction generator model.

As discussed above, the machine-learned prediction model can bepreviously trained via one or more machine-learning techniques. In someimplementations, the machine-learned prediction model can be previouslytrained by one or more devices (e.g., training computing system,operations computing system 104, one or more remote computing devices106, etc.) remote from the vehicle 108.

The motion planning system 128 can determine a motion plan and generatemotion plan data 134 for the vehicle 108 based at least in part on theprediction data 132 (and/or other data). The motion plan data 134 caninclude vehicle actions with respect to the objects proximate to thevehicle 108 as well as the predicted movements. For instance, the motionplanning system 128 can implement an optimization algorithm thatconsiders cost data associated with a vehicle action as well as otherobjective functions (e.g., cost functions based on speed limits, trafficlights, and/or other aspects of the environment), if any, to determineoptimized variables that make up the motion plan data 134. By way ofexample, the motion planning system 128 can determine that the vehicle108 can perform a certain action (e.g., pass an object) withoutincreasing the potential risk to the vehicle 108 and/or violating anytraffic laws (e.g., speed limits, lane boundaries, signage). The motionplan data 134 can include a planned trajectory, velocity, acceleration,and/or other actions of the vehicle 108.

The motion planning system 128 can provide the motion plan data 134 withdata indicative of the vehicle actions, a planned trajectory, and/orother operating parameters to the vehicle control systems 138 toimplement the motion plan data 134 for the vehicle 108. For instance,the vehicle 108 can include a mobility controller configured totranslate the motion plan data 134 into instructions. In someimplementations, the mobility controller can translate determined motionplan data 134 into instructions for controlling the vehicle 108including adjusting the steering of the vehicle 108 “X” degrees and/orapplying a certain magnitude of braking force. The mobility controllercan send one or more control signals to the responsible vehicle controlcomponent (e.g., braking control system, steering control system and/oracceleration control system) to execute the instructions and implementthe motion plan data 134.

The vehicle computing system 112 can include a communications system 136configured to allow the vehicle computing system 112 (and its one ormore computing devices) to communicate with other computing devices. Thevehicle computing system 112 can use the communications system 136 tocommunicate with the operations computing system 104 and/or one or moreother remote computing devices (e.g., the one or more remote computingdevices 106) over one or more networks (e.g., via one or more wirelesssignal connections). In some implementations, the communications system136 can allow communication among one or more of the system on-board thevehicle 108. The communications system 136 can also be configured toenable the autonomous vehicle to communicate with and/or provide and/orreceive data and/or signals from a remote computing device 106associated with a user and/or an item (e.g., an item to be picked-up fora courier service). The communications system 136 can utilize variouscommunication technologies including, for example, radio frequencysignaling and/or Bluetooth low energy protocol. The communicationssystem 136 can include any suitable components for interfacing with oneor more networks, including, for example, one or more: transmitters,receivers, ports, controllers, antennas, and/or other suitablecomponents that can help facilitate communication. In someimplementations, the communications system 136 can include a pluralityof components (e.g., antennas, transmitters, and/or receivers) thatallow it to implement and utilize multiple-input, multiple-output (MIMO)technology and communication techniques.

The vehicle computing system 112 can include the one or morehuman-machine interfaces 140. For example, the vehicle computing system112 can include one or more display devices located on the vehiclecomputing system 112. A display device (e.g., screen of a tablet, laptopand/or smartphone) can be viewable by a user of the vehicle 108 that islocated in the front of the vehicle 108 (e.g., driver's seat, frontpassenger seat). Additionally, or alternatively, a display device can beviewable by a user of the vehicle 108 that is located in the rear of thevehicle 108 (e.g., a back passenger seat). For example, the autonomycomputing system 120 can provide one or more outputs including agraphical display of the location of the vehicle 108 on a map of ageographical area within one kilometer of the vehicle 108 including thelocations of objects around the vehicle 108. A passenger of the vehicle108 can interact with the one or more human-machine interfaces 140 bytouching a touchscreen display device associated with the one or morehuman-machine interfaces.

In some implementations, the vehicle computing system 112 can performone or more operations including activating, based at least in part onone or more signals or data (e.g., the sensor data 116, the map data122, the perception data 130, the prediction data 132, and/or the motionplan data 134) one or more vehicle systems associated with operation ofthe vehicle 108. For example, the vehicle computing system 112 can sendone or more control signals to activate one or more vehicle systems thatcan be used to control and/or direct the travel path of the vehicle 108through an environment.

By way of further example, the vehicle computing system 112 can activateone or more vehicle systems including: the communications system 136that can send and/or receive signals and/or data with other vehiclesystems, other vehicles, or remote computing devices (e.g., remoteserver devices); one or more lighting systems (e.g., one or moreheadlights, hazard lights, and/or vehicle compartment lights); one ormore vehicle safety systems (e.g., one or more seatbelt and/or airbagsystems); one or more notification systems that can generate one or morenotifications for passengers of the vehicle 108 (e.g., auditory and/orvisual messages about the state or predicted state of objects externalto the vehicle 108); braking systems; propulsion systems that can beused to change the acceleration and/or velocity of the vehicle which caninclude one or more vehicle motor or engine systems (e.g., an engineand/or motor used by the vehicle 108 for locomotion); and/or steeringsystems that can change the path, course, and/or direction of travel ofthe vehicle 108.

Referring now to FIGS. 2 and 3, a LIDAR system 200 is provided accordingto example embodiments of the present disclosure. It should beunderstood that the LIDAR system 200 can be included as part of thesensors 114 discussed above with reference to FIG. 1. As shown, theLIDAR system 200 can include a plurality of LIDAR units 300. Forinstance, in some implementations, the LIDAR system 200 can include fourLIDAR units 300. In alternative implementations, the LIDAR system 200can include more or fewer LIDAR units 300. Each of the plurality ofLIDAR units 300 can include a housing 310 defining a cavity (not shown).Furthermore, each of the plurality of LIDAR units 300 can include aplurality of emitters (not shown) positioned within the cavity. Itshould be understood that each of the plurality of emitters can beconfigured to emit a laser beam. In this manner, a plurality of laserbeams 210 can be emitted from the housing 310 of each of the pluralityof LIDAR units 300.

As shown, the LIDAR system 200 can include a first optic 400. The firstoptic 400 can be rotatable about a first axis 202 at a first rotationalspeed. In some implementations, the first rotational speed can rangefrom 500 revolutions per minute to 700 revolutions per minute. The firstoptic 400 can be positioned relative to the plurality of LIDAR units 300such that the plurality of laser beams 210 exiting the housing 310 ofeach of the plurality of LIDAR units 300 pass through the first optic400. Furthermore, the first optic 400 can refract the plurality of laserbeams 210 such that the plurality of laser beams 210 exit the firstoptic 400 as a plurality of refracted laser beams 220.

The LIDAR system 200 can further include a second optic 500. The secondoptic 500 can be rotatable about a second axis 204 at a secondrotational speed. The second axis 204 can be substantially perpendicular(e.g., less than a 15 degree difference, less than a 10 degreedifference, less than a 5 degree difference, less than a 1 degreedifference, etc.) to the first axis 202. Furthermore, the secondrotational speed can be faster than the first rotational speed. Forinstance, in some implementations, the second rotational speed can rangefrom 3,300 revolutions per minute to 3,900 revolutions per minute.

The second optic 500 can be positioned within a path of the plurality ofrefracted laser beams 220 exiting the first optic 400. Furthermore, thesecond optic 500 can include a mirror. In this manner, the plurality ofrefracted laser beams 220 can reflect off the second optic 500 as aplurality of reflected laser beams 230. In some implementations, thesecond optic 500 can include a multi-sided mirror (e.g., double-sidedmirror, triple-sided mirror, etc.).

A field of regard of the second optic 500 can be wider than a field ofregard of the first optic 400. For instance, in some implementations,the field of regard of the second optic 500 can be about 180 degrees,whereas the field of regard of the first optic 400 can be about 80degrees. In this manner, the second optic 500 can widen a field ofregard of the LIDAR system 200 such that the LIDAR system 200 can scan alarger area without needing to physically move one or more of the LIDARunits 300.

Referring now to FIGS. 4 and 5, the plurality of laser beams 210 emittedfrom the housing 310 of each of the plurality of LIDAR units 300 (onlyone shown) can be spaced apart from one another by a first angulardistance 212. For instance, in some implementations, the first angulardistance 212 can be greater than 4 degrees. The first optic 400 can beconfigured to refract the plurality of laser beams 210 such that theplurality of refracted laser beams 220 exiting the first optic 400 arespaced apart from one another by a second angular distance 222 that isless than the first angular distance 212. In this manner, the resolutionof the LIDAR system 200 can be improved. In some implementations, thesecond angular distance 222 can be less than 2 degrees. In alternativeimplementations, the second angular distance 222 can be less than 1degree.

Referring now to FIGS. 6 and 7, an example embodiment of the first optic400 is provided according to example embodiments of the presentdisclosure. As shown, the first optic 400 can include a prism disk 410.The prism disk 410 can define a radial axis 412 and a vertical axis 414.The vertical axis 414 can be substantially perpendicular to the radialaxis 412. As shown, the prism disk 410 can include a plurality of wedges420. For instance, in some implementations, the prism disk 410 caninclude six wedges 420 (e.g., first wedge, second wedge, third wedge,fourth wedge, fifth wedge, and sixth wedge). In alternativeimplementations, the prism disk 410 can include more or fewer wedges420. For instance, in some implementations, the prism disk 410 caninclude only one wedge 420.

Each of the plurality of wedges 420 of the prism disk 410 can define adifferent wedge angle 430. For instance, the wedge angle 430 associatedwith a first wedge of the plurality of wedges 420 can be different thanthe wedge angle 430 associated with a second wedge of the plurality ofwedges 420. In some implementations, the wedge angle 430 for each of theplurality of wedges 420 can range from −5 degrees relative to the radialaxis 412 of the prism disk 410 to 5 degrees relative to the radial axis412 of the prism disk 410.

Referring now to FIGS. 8 and 9, the plurality of laser beams 210 exitingthe housing 310 of a first LIDAR unit of the plurality of LIDAR units300 and the plurality of laser beams 210 exiting the housing 310 of asecond LIDAR unit of the plurality of LIDAR units 300 can pass through afirst portion 440 of the prism disk 410. Conversely, the plurality oflaser beams 210 exiting the housing 310 of a third LIDAR unit of theplurality of LIDAR units 300 and the plurality of laser beams 210exiting the housing 310 of a fourth LIDAR unit of the plurality of LIDARunits 300 can pass through a second portion 450 of the prism disk 410.

As shown, the second portion 450 of the prism disk 410 can be differentthan the first portion 440 of the prism disk 410. More specifically, thefirst portion 440 of the prism disk 410 and the second portion 450 ofthe prism disk 410 can each include different wedges 420. For instance,in some implementations, the first portion 440 of the prism disk 410 caninclude a first wedge, a second wedge, and a third wedge. Conversely,the second portion 450 of the prism disk 410 can include a fourth wedge,a fifth wedge, and a sixth wedge. In some implementations, each of thewedges 420 (e.g., first wedge, second wedge, third wedge, fourth wedge,fifth wedge, sixth wedge) can be substantially the same size. In thismanner, the first portion 440 of the prism disk 410 and the secondportion 450 of the prism disk 410 can be symmetric relative to oneanother.

In some implementations, the housing 310 of each of the plurality ofLIDAR units 300 can be tilted relative to the first axis 202 such thatan angle 460 is defined therebetween. In some implementations, the angle460 can be about 45 degrees. For instance, the housing 310 of a firstLIDAR unit and the housing 310 of a second LIDAR unit can each be tiltedin a first direction (e.g., upward) relative to the first axis 202.Conversely, the housing 310 of a third LIDAR unit and the housing 310 ofa fourth LIDAR unit can each be tilted in a second direction (e.g.,downward) relative to the first axis 202.

Referring now to FIGS. 10 through 13, another LIDAR system 600 isprovided according to example embodiments of the present disclosure. Asshown, the LIDAR system 600 can include a first LIDAR unit 610 and asecond LIDAR unit 612. It should be understood that the first LIDAR unit610 and the second LIDAR unit 612 can be similar to the LIDAR units 300of the LIDAR system 200 discussed above with reference to FIGS. 2 and 3.For instance, the first LIDAR unit 610 and the second LIDAR unit 612 caneach include a housing 611 defining a cavity (not shown). Furthermore,the first LIDAR unit 610 and the second LIDAR unit 612 can each includea plurality of emitters 620 positioned within the cavity. It should beunderstood that each of the plurality of emitters 620 can be configuredto emit a laser beam. In this manner, a plurality of laser beams 630 canbe emitted from the housing 611 of the first LIDAR unit 610 and thehousing 611 of the second LIDAR unit 612.

As shown, the LIDAR system 600 can include a first prism disk 640 and asecond prism disk 642. The first prism disk 640 and the second prismdisk 642 can each be rotatable about a first axis 602 at a firstrotational speed. In some implementations, the first rotational speedcan range from 500 revolutions per minute to 700 revolutions per minute.The first prism disk 640 can be positioned relative to the first LIDARunit 610 such that the plurality of laser beams 630 exiting the firstLIDAR unit 610 pass through the first prism disk 640. Conversely, thesecond prism disk 642 can be positioned relative to the second LIDARunit 612 such that the plurality of laser beams 630 emitted from thesecond LIDAR unit 612 pass through the second prism disk 642.

The LIDAR system 600 can further include a mirror 650. The mirror 650can be rotatable about a second axis 604 at a second rotational speedthat is faster than the first rotational speed. For instance, in someimplementations, the second rotational speed can range from 3,300revolutions per minute to 3,900 revolutions per minute. The second axis604 can be substantially perpendicular (e.g., less than a 15 degreedifference, less than a 10 degree difference, less than a 5 degreedifference, less than a 1 degree difference, etc.) to the first axis602. As shown, the mirror 650 can have a plurality of reflectivesurfaces (e.g., three reflective surfaces). For instance, in someimplementations, the mirror 650 can include a first reflective surface652, a second reflective surface 654, and a third reflective surface656. In alternative implementations, the mirror 650 can include more orfewer reflective surfaces.

As shown, a plurality of refracted laser beams 660 exiting the firstprism disk 640 can reflect off the mirror 650. More specifically, theplurality of refracted laser beams 660 can reflect off the firstreflective surface 652 of the mirror 650 as a plurality of reflectedlaser beams 670. Additionally, a plurality of refracted laser beams 662exiting the second prism disk 642 can reflect off the mirror 650. Morespecifically, the plurality of refracted laser beams 662 exiting thesecond prism disk 642 can reflect off the second reflective surface 654of the mirror 640 as a plurality of reflected laser beams 672.

A field of regard of the mirror 650 can be wider than a field of regardof each of the first prism disk 640 and the second prism disk 642. Forinstance, in some implementations, the field of regard of the mirror 650can be about 180 degrees, whereas the field of regard of each of thefirst prism disk 640 and the second prism disk 642 can be about 80degrees. In this manner, the mirror 650 can widen the field of regard ofthe LIDAR system 600 such that the LIDAR system 600 can scan a largerarea without needing to physically move the first LIDAR unit 610, thesecond LIDAR unit 612, or both.

Referring now to FIGS. 14 and 15, the plurality of laser beams 630emitted from the housing 611 of the first LIDAR unit 610 and the housing611 of the second LIDAR unit 612 can be spaced apart from one another bya first angular distance 632. For instance, in some implementations, thefirst angular distance 632 can be greater than 4 degrees. The firstprism disk 640 can be configured to refract the plurality of laser beams630 emitted from the first LIDAR unit 610 such that the plurality ofrefracted laser beams 660 are spaced apart from one another by a secondangular distance 664 that is less than the first angular distance 632.Additionally, the second prism disk 642 can be configured to refract theplurality of laser beams 630 emitted from the second LIDAR unit 612 suchthat the plurality of refracted laser beams 662 are spaced apart fromone another from by the second angular distance 664. In this manner, theresolution of the LIDAR system 600 can be improved. In someimplementations, the second angular distance 664 can be less than 2degrees. In alternative implementations, the second angular distance 664can be less than 1 degree.

Referring now to FIGS. 16 and 17, a LIDAR unit 700 is provided accordingto example embodiments of the present disclosure. It should beunderstood that the LIDAR unit 700 can be used in conjunction with theLIDAR system 200 discussed above with reference to FIGS. 2 and 3 and theLIDAR system 600 discussed above with reference to FIGS. 10-12. Asshown, the LIDAR unit 700 can include a housing 710 defining a cavity712. The LIDAR unit 700 can further include a plurality of emitters 720disposed on a surface 732 of a circuit board 730 positioned within thecavity 712. In some implementations, the LIDAR unit 700 can include atotal of nine emitters 720. In alternative implementations, the LIDARunit 700 can include more or fewer emitters 720. Each of the pluralityof emitters 720 can be configured to emit a laser beam along a transmitpath 740 that is substantially perpendicular (e.g., less than a 15degree difference, less than a 10 degree difference, less than a 5degree difference, less than a 1 degree difference, etc.) to the surface732 of the circuit board 730.

The LIDAR unit 700 can include a first telecentric lens assembly 750.The first telecentric lens assembly 750 can be positioned within thecavity 712 of the housing 710 and along the transmit path 740. In thismanner, the laser beam emitted from each of the plurality of emitters720 can pass through the first telecentric lens assembly 750 beforeexiting the cavity 712. As shown, the LIDAR unit 700 can include asecond telecentric lens assembly 760 positioned within the cavity 712 ofthe housing 710. More specifically, the second telecentric lens assembly760 can be positioned along a receive path 770 that is substantiallyperpendicular to the surface 732 of the circuit board 730. In thismanner, a plurality of reflected laser beams entering the cavity 712from an outside environment can pass through the second telecentric lensassembly 760 positioned along the receive path 770.

It should be understood that the receive path 770 along which the secondtelecentric lens assembly 760 is positioned is different than thetransmit path 740 along which the first telecentric lens assembly 750 ispositioned. For instance, the receive path 770 can be located at a lowerportion of the cavity 712 defined by the housing 710, whereas thetransmit path 740 can be located at an upper portion of the cavity 712.Furthermore, in some implementations, the housing 710 of the LIDAR unit700 can include a partition wall 714 (denoted by dashed line) dividingthe cavity 712 into the upper portion and the lower portion.

The first telecentric lens assembly 750 can include multiple lenses. Forinstance, the first telecentric lens assembly 750 can include at least afirst lens 752 and a second lens 754. The first lens 752 can be a fieldflattening lens. In some implementations, the second lens 754 can be arefractive lens. The first lens 752 (e.g., field flattening lens) can bepositioned between the circuit board 730 and the second lens 754. Thefirst telecentric lens assembly 750 can eliminate the need for theplurality of emitters 720 to be disposed on a curved surface. In thismanner, the surface 732 of the circuit board 730 on which the pluralityof emitters 720 are disposed can be substantially flat (that is, notcurved). This can reduce complexity in manufacturing and assembly of thecircuit board 730.

The second telecentric lens assembly 760 can include multiple lenses.For instance, the second telecentric lens assembly 760 can include atleast a first lens 762 and a second lens 764. The first lens 762 can bea field flattening lens. In some implementations, the second lens 764can be a refractive lens. The first lens 762 (e.g., field flatteninglens) can be positioned between the circuit board 730 and the secondlens 764.

In some implementations, the first lens 752 (e.g., field flatteninglens) of the first telecentric lens assembly 750 can be thinner than thefirst lens 762 (e.g., field flattening lens) of the second telecentriclens assembly 760. For instance, in some implementations, the first lens752 (e.g., telecentric lens) of the first telecentric lens assembly 750can have a thickness of about 3 millimeters. Conversely, the first lens762 (e.g., telecentric lens) of the second telecentric lens assembly 760can have a thickness of about 4 millimeters.

As shown, the LIDAR unit 700 can include a plurality of detectors 780.Each of the plurality of detectors 780 can be configured to detect oneor more of the plurality of reflected laser beams entering the cavity712 from an outside environment. Furthermore, since the LIDAR unit 700includes the second telecentric lens assembly 760 disposed within thecavity 712 and along the receive path 770, the plurality of detectors780 need not be disposed on a curved surface. Instead, the plurality ofdetectors 780 can be disposed on the surface 732 of the circuit board730. In this manner, the plurality of emitters 720 and the plurality ofdetectors 780 can be disposed on the same surface 732 of the samecircuit board 730.

As shown, each of the plurality of detectors 780 can be spaced apartfrom a corresponding emitter of the plurality of emitters 720 by adistance 782. For instance, in some implementations, the distance 782can be about 4 millimeters. It should be understood that the pluralityof detectors 780 can include any suitable type of photodiode. Forinstance, in some implementations, each of the plurality of detectors780 can include an avalanche photodiode.

In some implementations, the LIDAR unit 700 can include an opticalfilter 790. It should be understood that the optical filter 790 caninclude any type of filter. For instance, in some implementations, theoptical filter 790 can be a bandpass filter. As shown, the opticalfilter 790 can be positioned within the cavity 712 and along the receivepath 770. More specifically, the optical filter 790 can be positionedbetween the plurality of detectors 780 and the first lens 762 (e.g.,field flattening lens) of the second telecentric lens assembly 760. Inthis manner, the optical filter 790 can have a narrow acceptance angle,because the plurality of reflected laser beams exiting the first lens762 (e.g., field flattening lens) of the second telecentric lensassembly 760 can be substantially perpendicular (e.g., less than a 15degree difference, less than a 10 degree difference, less than a 5degree difference, less than a 1 degree difference, etc.) to a surface692 of the optical filter 690. In some implementations, the acceptanceangle of the optical filter 690 can be about 2 degrees.

Referring briefly now to FIGS. 18 and 19, each of the plurality ofemitters 720 can include a laser diode 722 configured to emit a laserbeam 724. In some implementations, the laser diode 722 can be configuredto emit the laser beam 724 such that the laser beam 724 is substantiallyparallel (e.g., less than a 15 degree difference, less than a 10 degreedifference, less than a 5 degree difference, less than a 1 degreedifference, etc.) to the surface 732 of the circuit board 730. In suchimplementations, each of the plurality of emitters 720 can include acollimation lens 726. The collimation lens 726 can be positionedrelative to the laser diode 722 such that the laser beam 724 reflectsoff a surface of the collimation lens 726. More specifically, the laserbeam 724 can reflect off the surface of the collimation lens 726 suchthat the reflected laser beam 728 is substantially perpendicular to thecircuit board 730. In this manner, the reflected laser beam 728 can bedirected along the transmit path 740.

FIG. 20 depicts example system components of an example computing system800 according to example embodiments of the present disclosure. Theexample computing system 800 can include the vehicle computing system112 and one or more remote computing system(s) 850 that arecommunicatively coupled to the vehicle computing system 112 over one ormore network(s) 845. The computing system 800 can include one or morecomputing device(s) 810. The computing device(s) 810 of the vehiclecomputing system 112 can include processor(s) 815 and a memory 820. Theone or more processors 815 can be any suitable processing device (e.g.,a processor core, a microprocessor, an ASIC, a FPGA, a controller, amicrocontroller, etc.) and can be one processor or a plurality ofprocessors that are operatively connected. The memory 820 can includeone or more non-transitory computer-readable storage media, such as RAM,ROM, EEPROM, EPROM, one or more memory devices, flash memory devices,etc., and combinations thereof.

The memory 820 can store information that can be accessed by the one ormore processors 815. For instance, the memory 820 (e.g., one or morenon-transitory computer-readable storage mediums, memory devices) caninclude computer-readable instructions 825 that can be executed by theone or more processors 815. The computer-readable instructions 825 canbe software written in any suitable programming language or can beimplemented in hardware. Additionally, or alternatively, thecomputer-readable instructions 825 can be executed in logically and/orvirtually separate threads on processor(s) 815.

For example, the memory 820 can store the computer-readable instructions825 that, when executed by the one or more processors 815, cause the oneor more processors 815 to perform operations such as any of theoperations and functions for which the computing systems are configured,as described herein.

The memory 820 can store data 830 that can be obtained, received,accessed, written, manipulated, created, and/or stored. The data 830 caninclude, for instance, sensor data obtained via the LIDAR system 200,600 (shown in FIGS. 2 and 10, respectively), and/or otherdata/information described herein. In some implementations, thecomputing device(s) 810 can obtain from and/or store data in one or morememory device(s) that are remote from the computing system 800, such asone or more memory devices of the remote computing system 850.

The computing device(s) 810 can also include a communication interface835 used to communicate with one or more other system(s) (e.g., remotecomputing system 850). The communication interface 835 can include anycircuits, components, software, etc. for communicating via one or morenetworks (e.g., 845). In some implementations, the communicationinterface 835 can include for example, one or more of a communicationscontroller, receiver, transceiver, transmitter, port, conductors,software and/or hardware for communicating data/information.

The network(s) 845 can be any type of network or combination of networksthat allows for communication between devices. In some implementations,the network(s) 845 can include one or more of a local area network, widearea network, the Internet, secure network, cellular network, meshnetwork, peer-to-peer communication link and/or some combination thereofand can include any number of wired or wireless links. Communicationover the network(s) 845 can be accomplished, for instance, via a networkinterface using any type of protocol, protection scheme, encoding,format, packaging, etc.

FIG. 20 illustrates one example computing system 800 that can be used toimplement the present disclosure. Other computing systems can be used aswell without deviating from the scope of the present disclosure. The useof computer-based systems allows for a great variety of possibleconfigurations, combinations, and divisions of tasks and functionalitybetween and among components. Computer-implemented operations can beperformed on a single component or across multiple components.Computer-implemented tasks and/or operations can be performedsequentially or in parallel. Data and instructions can be stored in asingle memory device or across multiple memory devices.

Computing tasks discussed herein as being performed at computingdevice(s) remote from the vehicle can instead be performed at thevehicle (e.g., via the vehicle computing system), or vice versa. Suchconfigurations can be implemented without deviating from the scope ofthe present disclosure.

Referring now to FIG. 21, a block diagram of the LIDAR system 200, 600is provided according to example embodiments of the present disclosure.It should be understood that the LIDAR system 200, 600 can be includedas part of the sensors 114 discussed above with reference to FIG. 1. Asshown, the LIDAR system 200, 600 can include multiple channels 910;specifically, channels 1-N are illustrated. It should be understood thatchannels 1-N can be included in a single LIDAR unit 300 or may be spreadacross multiple LIDAR units 300. Each channel 910 can output point datathat provides a single point of ranging information. The point dataoutput by each of the channels 910 (e.g., point data_(1-N)) can becombined to create a point cloud that corresponds to a three-dimensionalrepresentation of the surrounding environment.

As shown, each channel 910 can include an emitter 920 paired with areceiver 930. The emitter 920 emits a laser signal into the environmentthat is reflected off the surrounding environment and returned back to adetector 832 (e.g., an optical detector) of the receiver 930. Eachemitter 920 can have an adjustable power level that controls anintensity of the emitted laser signal. The adjustable power level allowsthe emitter 920 to be capable of emitting the laser signal at one ofmultiple different power levels (e.g., intensities).

The detector 932 can provide the return signal to a read-out circuit934. The read-out circuit 934 can, in turn, output the point data basedon the return signal. The point data can indicate a distance the LIDARsystem 200, 600 is from a detected object (e.g., road, pedestrian,vehicle, etc.) that is determined by the read-out circuit 934 bymeasuring time-of-flight (ToF), which is the time elapsed time betweenthe emitter 920 emitting the laser signal (e.g., laser beam) and thereceiver 930 detecting the return signal (e.g., reflected laser beam).

The point data further includes an intensity value corresponding to eachreturn signal. The intensity value indicates a measure of intensity ofthe return signal determined by the read-out circuit 934. As notedabove, the intensity of the return signal provides information about thesurface reflecting the signal and can be used by the autonomy computingsystem 120 (FIG. 1) for localization, perception, prediction, and/ormotion planning. The intensity of the return signals depends on a numberof factors, such as the distance of the LIDAR system 200, 600 to thedetected object, the angle of incidence at which the emitter 920 emitsthe laser signal, temperature of the surrounding environment, thealignment of the emitter 920 and the receiver 930, and the reflectivityof the detected surface.

As shown, a reflectivity processing system 940 receives the point datafrom the LIDAR system 200, 600 and processes the point data to classifyspecular reflectivity characteristics of objects. The reflectivityprocessing system 940 classifies the specular reflectivitycharacteristics of objects based on a comparison of reflectivity valuesderived from intensity values of return signals. In some embodiments,the LIDAR system 200, 600 can be calibrated to produce the reflectivityvalues. For example, the read-out circuit 934 or another component ofthe LIDAR system 200, 600 can be configured to normalize the intensityvalues to produce the reflectivity values. In these embodiments, thereflectivity values may be included in the point data received by thereflectivity processing system 940 from the LIDAR system 200, 600. Inother embodiments, the reflectivity processing system 940 may generatethe reflectivity values based on intensity return values included in thepoint data received from the LIDAR system 200, 600.

Regardless of which component is responsible for generating thereflectivity values, the process for doing so may, in some embodiments,include using a linear model to compute one or more calibrationmultipliers and one or more bias values to be applied to returnintensity values. Depending on the embodiment, a calibration multiplierand bias value may be computed for and applied to each channel of theLIDAR system 200, 600 at each power level. The linear model assumes auniform diffuse reflectivity for all surfaces and describes an expectedintensity value as a function of a raw intensity variable, a calibrationmultiplier variable, and/or a bias variable. The computing of thecalibration multiplier and bias value for each channel/power levelcombination includes determining a median intensity value based on theraw intensity values output by the channel at the power level and usingthe median intensity value as the expected intensity value in the linearmodel while optimizing values for the calibration multiplier variableand bias variable. As an example, the calibration multiplier and biasvalue may be computed by solving the linear model using an IteratedRe-weighted Least Squares approach.

The calibration multiplier and bias value computed for each channel 910at each power level can be assigned to the corresponding channel/powerlevel combination. In this way, each power level of each channel of theLIDAR system 200, 600 can have an independently assigned calibrationmultiplier and bias value from which reflectivity values may be derived.Once assigned, the calibration multiplier and bias value of eachchannel/power level combination can be used at run-time to determinereflectivity values from subsequent intensity values produced by thecorresponding channel at the corresponding power level during operationof an autonomous or semi-autonomous vehicle. More specifically,reflectivity values can be determined from the linear model by using thevalue of the calibration multiplier and the bias value for thecalibration multiplier variable and bias variable, respectively. In thismanner, the intensity values can be normalized to be more aligned withthe reflectivity of a surface by taking into account factors such as thedistance of the LIDAR system 200, 600 to the detected surface, the angleof incidence at which the emitter 920 emits the laser signal,temperature of the surrounding environment, and/or the alignment of theemitter 920 and the receiver 930.

Referring now to FIG. 22, a flowchart diagram of an example method 1000of controlling operation of an autonomous vehicle having a LIAR systemis provided according to example embodiments of the present disclosure.One or more portion(s) of the method 1000 can be implemented by acomputing system that includes one or more computing devices such as,for example, the computing systems described with reference to the otherfigures (e.g., the vehicle computing system 112, the operationscomputing system 104, the one or more remote computing devices 106,etc.). Each respective portion of the method 1000 can be performed byany (or any combination) of one or more computing devices. Moreover, oneor more portion(s) of the method 1000 can be implemented as an algorithmon the hardware components of the device(s) described herein to, forexample, control operation of the autonomous vehicle according to dataobtained from the LIDAR system.

FIG. 22 depicts elements performed in a particular order for purposes ofillustration and discussion. Those of ordinary skill in the art, usingthe disclosures provided herein, will understand that the elements ofany of the methods discussed herein can be adapted, rearranged,expanded, omitted, combined, and/or modified in various ways withoutdeviating from the scope of the present disclosure. FIG. 19 is describedwith reference to elements/terms described with respect to other systemsand figures for exemplary illustrated purposes and is not meant to belimiting. One or more portions of method 900 can be performedadditionally, or alternatively, by other systems.

At (1002), the method 1000 can include obtaining, via the LIDAR system,sensor data indicative of an object within a field of view of the LIDARsystem. As described herein, wherein the LIDAR system can include one ormore LIDAR units including a housing defining a cavity and one or moreemitters disposed within the cavity. Each of the one or more emitterscan be configured to emit one or more laser beams. The LIDAR system caninclude a prism disk rotatable about a first axis at a first rotationalspeed. The prism disk can be configured to refract the one or more laserbeams emitted from the one or more emitters. The LIDAR system caninclude a mirror rotatable about a second axis at a second rotationalspeed. The mirror can be positioned relative to the prism disk such thateach of the one or more laser beams exiting the prism disk reflect offof the mirror, as described herein.

Additionally, or alternatively, the LIDAR system can include a LIDARunit. The LIDAR unit can include: a housing defining a cavity, one ormore emitters positioned within the cavity and configured to emit one ormore laser beams along a transmit path, a first telecentric lens alongthe transmit path, a second telecentric lens along a receive path, andone or more detectors configured to detect one or more reflected laserbeams entering the cavity, as described herein.

At (1004), the method 1000 can include determining perception data forthe object based, at least in part, on the sensor data obtained at(902). The perception data can describe, for example, an estimate of theobject's current and/or past: location and/or position; speed; velocity;acceleration; heading; orientation; size/footprint (e.g., as representedby a bounding shape); class (e.g., pedestrian class vs. vehicle classvs. bicycle class); and/or other state information.

At (1006), the method 1000 can include determining one or more futurelocations of the object based, at least in part, on the perception datafor the object. For example, the autonomous vehicle can generate atrajectory (e.g., including one or more waypoints) that is indicative ofa predicted future motion of the object, given the object's heading,velocity, type, etc. over current/previous timestep(s).

At (1008), the method 1000 can include determining an action for theautonomous vehicle based at least in part on the one or more futurelocations of the object. For example, the autonomous vehicle cangenerate a motion plan that includes a vehicle trajectory by which thevehicle can travel to avoid interfering/colliding with the object. Inanother example, the autonomous vehicle can determine that the object isa user that intends to enter the autonomous vehicle (e.g., for a humantransportation service) and/or that intends place an item in theautonomous vehicle (e.g., for a courier/delivery service). Theautonomous vehicle can unlock a door, trunk, etc. to allow the user toenter and/or place an item within the vehicle. The autonomous vehiclecan communicate one or more control signals (e.g., to a motion controlsystem, door control system, etc.) to initiate the determined actions.

While the present subject matter has been described in detail withrespect to specific example embodiments and methods thereof, it will beappreciated that those skilled in the art, upon attaining anunderstanding of the foregoing can readily produce alterations to,variations of, and equivalents to such embodiments. Accordingly, thescope of the present disclosure is by way of example rather than by wayof limitation, and the subject disclosure does not preclude inclusion ofsuch modifications, variations and/or additions to the present subjectmatter as would be readily apparent to one of ordinary skill in the art.

What is claimed is:
 1. A light detection and ranging (LIDAR) unitcomprising: a housing defining a cavity; a plurality of emittersdisposed on a surface of a circuit board positioned within the cavity,each of the plurality of emitters configured to emit a laser beam alonga transmit path; a first telecentric lens assembly positioned within thecavity and along the transmit path such that the laser beam emitted fromeach of the plurality of emitters passes through the first telecentriclens assembly, the first telecentric lens assembly comprising a firstfield flattening lens and at least one other lens; a second telecentriclens assembly positioned within the cavity and along a receive path suchthat a plurality of reflected laser beams entering the cavity passthrough the second telecentric lens assembly, the second telecentriclens assembly comprising a second field flattening lens and at least oneother lens; and a plurality of detectors disposed on the surface of thecircuit board, each of the plurality of detectors spaced apart from acorresponding emitter of the plurality of emitters, each of theplurality of detectors configured to detect one or more of the pluralityof reflected laser beams.
 2. The LIDAR unit of claim 1, wherein: thefirst field flattening lens is positioned between the plurality ofemitters and the at least one other lens of the first telecentric lensassembly; and the second field flattening lens is positioned between theplurality of detectors and the at least one other lens of the secondtelecentric assembly.
 3. The LIDAR unit of claim 1, further comprising:an optical filter disposed within the cavity such that the opticalfilter is positioned along the receive path between the plurality ofdetectors and the second field flattening lens.
 4. The LIDAR unit ofclaim 3, wherein the optical filter comprises a bandpass filter.
 5. TheLIDAR unit of claim 3, wherein the plurality of reflected laser beamsexiting the second field flattening lens are substantially perpendicularto a surface of the optical filter.
 6. The LIDAR unit of claim 5,wherein an acceptance angle of the optical filter is about 2 degrees. 7.The LIDAR unit of claim 1, wherein each of the plurality of detectors isspaced apart from the corresponding emitter of the plurality of emittersby a distance of about 4 millimeters.
 8. The LIDAR unit of claim 1,wherein each of the plurality of emitters comprise: a laser diodeconfigured to emit the laser beam such that the laser beam issubstantially parallel to the circuit board; and a collimation lenspositioned relative to the laser diode such that the laser beam emittedfrom the laser diode reflects off of the collimation lens and along thetransmit path.
 9. The LIDAR unit of claim 1, wherein the surface of thecircuit board is substantially flat.
 10. The LIDAR unit of claim 1,wherein each of the plurality of detectors comprises an avalanchephotodiode.
 11. The LIDAR unit of claim 2, wherein the first telecentriclens is thinner than the second telecentric lens.
 12. The LIDAR unit ofclaim 11, wherein: the first field flattening lens has a thickness ofabout 3 millimeters; and the second field flattening lens has athickness of about 4 millimeters.
 13. An autonomous vehicle comprising:one or more LIDAR units coupled to a vehicle body of the autonomousvehicle, the one or more LIDAR units comprising: a housing defining acavity; a plurality of emitters disposed on a surface of a circuit boardpositioned within the cavity, each of the plurality of emitterscomprising a laser diode configured to emit a laser beam such that thelaser beam is substantially perpendicular to the circuit board, each ofthe plurality of emitters further comprising a collimation lenspositioned relative to the laser diode such that the laser beam emittedfrom the laser diode reflects off of the collimation lens and along atransmit path; a first telecentric lens assembly positioned within thecavity along the transmit path such that the laser beam emitted fromeach of the plurality of emitters passes through the first telecentriclens assembly, the first telecentric lens assembly comprising a firstfield flattening lens and at least one other lens; a second telecentriclens assembly positioned within the cavity along a receive path suchthat a plurality of reflected laser beams entering the cavity passthrough the second telecentric lens assembly, the second telecentriclens assembly comprising a second field flattening lens and at least oneother lens; and a plurality of detectors disposed on the surface of thecircuit board, each of the plurality of detectors spaced apart from acorresponding emitter of the plurality of emitters, each of theplurality of detectors configured to detect one or more of the pluralityof reflected laser beams.
 14. The autonomous vehicle of claim 13,wherein: the first field flattening lens is positioned between theplurality of emitters and the at least one other lens of the firsttelecentric assembly; and the second field flattening lens is positionedbetween the plurality of detectors and the at least one other lens ofthe second telecentric assembly.
 15. The autonomous vehicle of claim 14,wherein the one or more LIDAR units further comprise: an optical filterdisposed within the cavity such that the optical filter is positionedbetween the plurality of detectors and the second field flattening lens.16. The autonomous vehicle of claim 14, wherein the first fieldflattening lens is thinner than the second field flattening lens. 17.The autonomous vehicle of claim 14, wherein the surface of the circuitboard is substantially flat.
 18. The autonomous vehicle of claim 14,wherein each of the plurality of detectors comprises an avalanchephotodiode.
 19. A computing system comprising: one or more processors;and one or more tangible, non-transitory, computer readable media thatcollectively store instructions that, when executed by the one or moreprocessors, cause the computing system to perform operations, theoperations comprising: obtaining sensor data indicative of an objectwithin a field of view of a LIDAR system onboard an autonomous vehicle,wherein the LIDAR system comprises a LIDAR unit, the LIDAR unitcomprising: a housing defining a cavity, one or more emitters positionedwithin the cavity and configured to emit one or more laser beams along atransmit path, a first telecentric lens assembly along the transmitpath, a second telecentric lens assembly along a receive path, and oneor more detectors configured to detect one or more reflected laser beamsentering the cavity; determining perception data for the object based atleast in part on the sensor data; determining one or more futurelocations of the object based at least in part on the perception datafor the object; and determining an action for the autonomous vehiclebased, at least in part, on the one or more future locations of theobject.
 20. The computing system of claim 19, wherein: the firsttelecentric lens assembly comprises a first field flattening lens and atleast one other lens, the first field flattening lens positioned betweenthe at least one other lens and the one or more emitters; and the secondtelecentric lens assembly comprises a second field flattening lens andat least one other lens, the second field flattening lens positionedbetween the at least one other lens of the second telecentric lensassembly and the one or more detectors.